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Record W2953842394 · doi:10.1021/acs.jafc.9b03079

Anti-inflammatory Effect and Cellular Uptake Mechanism of Peptides from Common Bean (<i>Phaseolus vulga</i> L.) Milk and Yogurts in Caco-2 Mono- and Caco-2/EA.hy926 Co-culture Models

2019· article· en· W2953842394 on OpenAlexafffund
Yuhuan Chen, Hua Zhang, Lili Mats, Ronghua Liu, Zeyuan Deng, Yoshinori Mine, Rong Tsao

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaChina Scholarship Council
KeywordsCaco-2PhaseolusPeptideValineLeucineBiochemistryChemistryBioavailabilityCell cultureTumor necrosis factor alphaCellBiologyPharmacologyAmino acidEndocrinology

Abstract

fetched live from OpenAlex

The bioavailability and anti-inflammatory activity of the phenolic compounds derived from gastrointestinal digestates of navy bean and light red kidney bean milks and yogurts were investigated in both Caco-2 mono- and Caco-2/EA.hy926 co-culture cell models. Instead of being transported directly, the ferulic acid ester derivatives in common bean milks and yogurts were found to be metabolized into ferulic acid and then be transported through the Caco-2 cell monolayer with an average basolateral ferulic acid concentration of 56 ± 3 ng/mL after 2 h. Strong anti-inflammatory effects were observed in the basolateral EA.hy926 cells of the co-culture model, and modulations of oxLDL-induced inflammatory mediators by the transported phenolics were verified to be through the p38 MAPK pathway. The present results suggest that the common bean-derived phenolics can be metabolized and absorbed by the intestinal epithelial cells and have antioxidant and anti-inflammatory effects against oxidative stress injury in vascular endothelial cells, hence contributing to the amelioration of vascular diseases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.190
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations43
Published2019
Admission routes2
Has abstractyes

Explore more

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